Performance of BDS Navigation Ionospheric Model During the Main Phase of Different Classified Geomagnetic Storms in China Region

© 2020. American Geophysical Union. All Rights Reserved. Geomagnetic storms can have a great impact on the Earth's upper atmosphere, that is, the ionosphere. The activity of the ionosphere could be more pronounced during geomagnetic storms, which can make key ionospheric parameters, like total electron content (TEC), very hard to be modeled. The use of a Global Navigation Satellite System (GNSS) navigation ionospheric model is a conventional option for users to correct the ionospheric delay, which could suffer from the effects of storms. In this study, the performance of Beidou Navigation Satellite System (BDS) navigation ionospheric model in the China region during the main phase of different classes of geomagnetic storms is investigated for the first time. The analysis of the results revealed that the accuracy of the BDS navigation ionospheric model was impacted to different degrees during the storms. The effects during strong storms were the greatest, followed by moderate and weak storms. The impact on the accuracy of the model was characterized by latitude and local time. Furthermore, the accuracy of the model during the same class of storms was not always at the same level. The finding in this study could benefit the prediction of GNSS navigation ionospheric models' performance during geomagnetic storms

Comparative phylogeography of the plateau zokor (Eospalax baileyi) and its host-associated flea (Neopsylla paranoma) in the Qinghai-Tibet Plateau

Background: Specific host-parasite systems often embody a particular co-distribution phenomenon, in which the parasite’s phylogeographic pattern is dependent on its host. In practice, however, both congruent and incongruent phylogeographic patterns between the host and the parasite have been reported. Here, we compared the population genetics of the plateau zokor (Eospalax baileyi), a subterranean rodent, and its host-associated flea species, Neopsylla paranoma, with an aim to determine whether the two animals share a similar phylogeographic pattern. Results: We sampled 130 host-parasite pairs from 17 localities in the Qinghai-Tibet Plateau (QTP), China, and sequenced a mitochondrial DNA (mtDNA) segment (~2,500 bp), including the complete COI and COII genes. We also detected 55 zokor and 75 flea haplotypes. AMOVA showed that the percentage of variation among the populations of zokors constituted 97.10%, while the within population variation was only 2.90%; for fleas, the values were 85.68% and 14.32%, respectively. Moreover, the flea Fst (fixation index) values were significantly smaller than in zokor. Although the Fst values between zokors and fleas were significantly and positively correlated (N =105, R =0.439, p =0.000), only a small amount (R2= 0.19) of the flea Fst variations could be explained by the zokor Fst variations. The two animals showed very distinct haplotype network structures from each other while co-phylogenetic analyses were unable to reject the hypothesis of an independence of speciation events. Conclusions: Zokors and fleas have very distinct population genetic patterns from each other, likely due to the influence of other sympatrically-distributed vertebrates on the transmission of fleas

Multiple Model Adaptive Nonlinear Observer of Dynamic Positioning Ship

Considering the filtering problem of dynamic positioning (DP) ship for the slowly varying sea state, a multiple model adaptive observer (MMAO) for dynamic positioning ship is presented. The MMAO consists of a bank of nonlinear subobserver and a dynamic weighting signal generator, in which each sub-observer is designed based on different peak frequency of wave spectrum model. To improve the performance of the observer, subobserver using the measurement of position, velocity, and acceleration is used to update the estimated velocity of ship. The observer parameters are optimized using particle swarm optimization (PSO). Finally, the method is verified effective by the computer simulation

Affine Formation Maneuver Control for Multi-Heterogeneous Unmanned Surface Vessels in Narrow Channel Environments

This paper investigates the affine formation maneuver control for multi-heterogeneous unmanned surface vessels (USV), aiming to enable them to navigate through narrow channels in the near-sea environment. The approach begins with implementing an affine transformation to facilitate flexible configuration adjustments within the formation system. The affine transformation of the entire formation is achieved by controlling the leaders’ positions. Second, this article introduces an anti-perturbation formation tracking controller for the underactuated vessels, which assume the role of leaders, to accurately follow the arbitrary formation transformation. Third, the followers consist of fully actuated vessels with the same kinematic model as the leaders but different dynamic models. This paper utilizes the affine localizability theorem to derive an expected virtual time-varying trajectory based on the leaders’ trajectory. The followers achieve the desired formation maneuver control by tracking this expected virtual time-varying trajectory through an anti-perturbation formation tracking controller. Finally, the efficacy of the introduced control law is confirmed and supported by the results obtained from rigorous simulation experiments

Control Allocation-Based Robust Tracking Control for Overactuated Surface Vessels Subject to Time-Varying Full-State Constraints

In this paper, we propose a robust tracking control scheme for trajectory tracking of overactuated marine surface vessels subject to environmental disturbances and asymmetric time-varying full-state constraints. The proposed robust control scheme is based on the unified barrier function technique that converts the original constrained dynamic positioning system into an equivalent nonconstrained one. In contrast to barrier Lyapunov function-based methods, the unbreakable requirement on the constraints is less restrictive, and the resultant controller is much simpler in this paper. The effect of environmental disturbances is compensated by a double-layer adaptive sliding mode disturbance observer. On the basis of the proposed adaptive disturbance observer, unknown lumped uncertainty can be estimated in finite time without knowing the upper bounds of the derivative of the lumped uncertainty. Since the surface vessel is overactuated, a control allocation scheme is required to distribute the generalized force signal to the actuators. The enhanced redistributed pseudoinverse algorithm is employed to ensure that the generalized force can be redistributed among the redundant actuators. Lastly, a simulation study is carried out on a dynamic positioning ship to verify the effectiveness of the proposed control method

Estimation of Observer Parameters for Dynamic Positioning Ships

Considering the problem of dynamic positioning systems for the slowly varying disturbances, a parametrically adaptive observer is presented. The peak frequency of observer is adjusted on-line by autoregressive (AR) spectral estimation; other parameters of observer are optimized using particle swarm optimization (PSO). The peak frequency can be calculated by spectral analysis of the pitch, roll, and heave measurements. In the spectral estimation, Levinson-Durbin algorithm is used to solve the Yule-Walker equations. Finally, the computer simulation is given to demonstrate the effectiveness of the proposed method

Fault-Tolerant Supervisory Control for Dynamic Positioning of Ships

A fault-tolerant supervisory control method for dynamic positioning of ships with actuator failures and sensor failures is presented in this paper. Unlike the traditional fault detection and control, fault detection and fault-tolerant controller are designed as a unit in this paper through a supervisor. By introducing a nonlinear estimation error and virtual controller, the sensor failures are separated from the actuator failures in the supervisory control system. It guarantees that the detectability property and matching property of the switched system are satisfied. Firstly, a new extended state observer is designed to match the models of different actuator failures. Secondly, by introducing a virtual controller, the detectability property of the switched system is guaranteed. Finally, a nonlinear estimation error operator is used in the designing of switching logic to guarantee stability of the closed-loop system with sensor failures. When sensor failures and actuator failures occur, we show that all the states of the closed-loop system are guaranteed to be bounded. The effectiveness of the fault-tolerant control is verified by simulation experiments